# Flappy-bird-deep-Q-learning-pytorch

**Repository Path**: jeave/Flappy-bird-deep-Q-learning-pytorch

## Basic Information

- **Project Name**: Flappy-bird-deep-Q-learning-pytorch
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-12-24
- **Last Updated**: 2021-11-03

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# [PYTORCH] Deep Q-learning for playing Flappy Bird

## Introduction

Here is my python source code for training an agent to play flappy bird. It could be seen as a very basic example of Reinforcement Learning's application.
<p align="center">
  <img src="demo/flappybird.gif" width=600><br/>
  <i>Camera app demo</i>
</p>

## How to use my code

With my code, you can:
* **Train your model from scratch** by running **python train.py**
* **Test your trained model** by running **python test.py**

## Trained models

You could find my trained model at **trained_models/flappy_bird**
 
## Requirements

* **python 3.6**
* **pygame**
* **cv2**
* **pytorch** 
* **numpy**